' start_date ': dt.datetime(year=2021, month=1, day=1, hour=11, minute=10 ),ĭummyOperator(task_id= ' start ') > DummyOperator(task_id= ' end ') ' schedule_interval ': dt.timedelta(days=1 ), ' dag_id ': ' schedule_interval_bug_example_dag ' , Time zone information is exposed and it is up to the writer of DAG what do with it.įrom _operator import DummyOperator Also templates used in Operators are not converted. There it will always be displayed in UTC. At the moment Airflow does not convert them to the end user’s time zone in the user interface. It allows you to run your DAGs with time zone dependent schedules.
Airflow stores datetime information in UTC internally and in the database. Support for time zones is enabled by default. S = sched.scheduler(time.time, time.sleep) # "execution_date": None, # "state": None, " conf " : # "dag_run_id": dag_run_id, " execution_date " : exec_time, # datetime object containing current date and timeĭt_string = now.strftime( " %Y-%m-%dT%H:%M:%SZ " )ĭag_id = " kmeans_with_workflow " def trigger_dag(): From Airflow 2.0.0, the Scheduler also uses Serialized DAGs for consistency and makes scheduling decisions.Īs shown in the image above, when using this feature, the DagFileProcessorProcess in the Scheduler parses the DAG files, serializes them in JSON format and saves them in the Metadata DB as SerializedDagModel model. In order to make Airflow Webserver stateless, Airflow >=1.10.7 supports DAG Serialization and DB Persistence. My last resort would be to programmatically create a py file containing the DAG definition that I want to publish and save this file to the $AIRFLOW_HOME/dags folder.
#TRIGGER AIRFLOW DAG FROM PYTHON CODE#
I want to be able to publish and trigger a DAG object from my code which is not in control of scheduler (viz. If you want to trigger this dag manually then you need to set scheduling_interval=None and use airflow trigger_dag dag_id (Documentation : airflow trigger dag) Please raise an issue in github if you encounter any such issues. NOTE: The Apache Airflow Client is still under active development and some methods or APIs might be broken. 项目还在开发，有些API是坏的。 Apache Airflow Python Client If you try to modify the field of an existing object, the request fails with an BAD_REQUEST error. The value of this field can be set only when creating the object. JSON object describing additional configuration parameters.
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